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Abstract

Background

Physical activity (PA) in children has declined in recent decades, highlighting the
need for effective intervention programs for school-aged children. The main objective
of this study was to assess to what extent PA during and after school hours changed
among children who received a progressive two-year long intervention vs. that of children who only received general curriculum-based PA.

Methods

A cluster randomized intervention study was conducted and six elementary schools randomly
assigned to serve as control- or intervention schools. All children attending second
grade (mean age = 7.4 years - born in 1999) were invited to participate in the fall
of 2006 (N = 320, 82% participated), again in 2007 (midpoint) and 2008 (end of intervention).
The intervention consisted of multi-component PA-intervention during school hours
and was conducted by teachers at each intervention school. PA was assessed by means
of accelerometers and subjectively at the intervention schools via teachers' PA log-books.

Results

There was no difference in PA intensity (minutes of moderate-to-vigorous physical
activity - min of MVPA) between the two study groups at baseline, but children in
the intervention schools were more physically active at moderate-to-vigorous intensity
compared to those in control schools after one year of intervention (mean difference
of MVPAlog-minutes: 0.61, 95%CI: 0.02, 1.20, p = 0.04). Moreover, the model for minutes of MVPA during
school hours, showed a significant three-way interaction between time at mid-point,
group and gender (mean difference of MVPAlog-minutes: 1.06, 95%CI: 0.15, 1.97, p = .02), indicating a significantly greater increase among
the boys in the intervention schools compared to girls. No difference in PA was detected
between the study groups at the end of the study period after two years of intervention.

Conclusions

The results suggest that the objective of increasing PA at school was met after one
year of intervention, and it was more pronounced among boys. The lack of increase
at the end of the study period suggested that any increase in PA during school may
highly depend on both motivation and training of general teachers. Boys may respond
better to PA interventions such as the one described in this study.

Background

A vast amount of research has confirmed that physical inactivity is an important factor
in the causal mechanisms of major chronic diseases such as obesity, cardiovascular
diseases, diabetes, and more [1]. In light of these negative health effects of an inactive lifestyle it is alarming
to find information which indicates a decline in children's physical activity in recent
decades [2]. Secular trends of physical activity patterns in Icelandic children are scarce, but
results from a cohort of 9 and 15-year old children showed that only a small proportion
of students at this age reached the recommended physical activity guidelines [3]. Consequently, this highlights the need for effective intervention programs that
focus on increasing both the amount and intensity of physical activity related behavior
among school-aged children. This need is even more evident in light of the progression
and prevalence of overweight and obesity among Icelandic children in recent years
[4].

Schools are generally considered ideal settings for the promotion of physical activity
and healthy lifestyle for several reasons, such as the ease of repeated access to
a large number of children, the somewhat controlled environment of the school, and
the general lack of cost to families [5,6]. However, recent systematic reviews of school-based physical activity intervention
studies show somewhat disappointing results [7,8]. These reviews highlight the need for studies of high methodological quality. Common
weaknesses in school-based interventions studies involve a lack of objective measures
of physical activity, the quality of physical activity administered and lack of statistical
power to detect differences. The majority of school-based physical activity interventions
carried out to date have relied on self-reported physical activity. This may have
caused differential misclassification in levels of physical activity introduced by
social desirability bias, which can be induced by the intervention itself [9]. However, there are intervention studies that measured children's and adolescents'
physical activity with objective instruments such as accelerometers [10-15] but they show inconsistent results. A recent study reported a highly effect intervention-program
among elementary school children which relied on a multi-component physical activity
program, including re-structuring three physical education lessons each week and adding
two extra lessons a week, daily short activity breaks, and physical activity homework
[15]. Despite being a very promising study it may prove difficult for an intervention
of this sort to become widespread because of the cost to schools which must allocate
more of their resources and time to provide students with two extra PE lessons per
week.

Due to the potential influence of local environmental factors, culture and educational
setting on any school-based intervention program, it is important to build an evidence
base within each country. In Iceland, no study of this kind has been conducted to
date. It is thus important to provide knowledge to this field that is applicable to
local circumstances.

The research question asked in this study was how much a two-year progressive teacher-led
physical activity intervention could affect physical activity during school hours
and physical activity after school hours among 7-year Icelandic children. Thus, the
objectives of this study were to compare changes in volume and intensity of physical
activity among the group of intervention children to physical activity levels of children
who only received general curriculum-based physical activity (controls) and further,
to assess whether the intervention effect on physical activity was modified by gender
or BMI?

Methods

Study Design and Participants

Eight months before the baseline measurements three pairs of schools in the city of
Reykjavik were selected and matched on size, i.e. number of students and total number
of grades. Thus, four large schools with grades one to ten and two schools with only
grades one to seven, with at least 30 students entering the second grade in 2006 were
sent letters of participation, which they all accepted. Then, one of the schools in
each pair was randomly selected to serve as an intervention school, leaving the other
as a control school. All children attending second grade (N = 321, born in 1999) were
invited to participate and to hand in a written consent form. Figure 1 shows the flow of participants through the three measurement sessions of the study.

Figure 1.Chart describing school and participant flow through the study.

The intervention started immediately after baseline measurements. All children in
the second grade of the participating intervention schools received the intervention,
regardless of whether they consented to undergo physical measurements or not. The
intervention focused on two major components of a healthy lifestyle: physical activity
and a healthy diet for all. The latter component is not described here. The implementation
of this study was approved by The National Bioethics Committee and the Icelandic Data
Protection Commission (VSN b200605002&03).

The same three PE teachers (all certified PE teachers) at each intervention school
took part in the study throughout the two-year intervention period. At any given time
a total of eight general teachers implemented the intervention, three in two of the
intervention schools, but two in the third school.

Background to intervention

The foundation of the school-based physical activity intervention in this study was
built upon the constructs of social cognitive theory [16]. According to the theory we may learn new behavior via observational learning of
various social factors and interactions in our environment. We are likelier to imitate
and adopt certain behaviors if we observe positive, desired outcomes in the behavior
under examination. We are even likelier to pursue these behaviors if they are modeled
by someone we know or someone we relate to. Individuals who repeatedly play the role
of such models are teachers, who often possess important qualities, which they utilize
to positively affect their students' learning. This process has been proven useful
for understanding the nature of physical activity by considering a person's experiences,
behavior skills and the context in which the person is expected to be active [17].

Intervention objectives and implementation

The primary objective of the physical activity intervention was to progressively increase
the amount of physical activity behavior at school such that all children in the intervention
schools would have the opportunity to engage in some form of physical activity for
a minimum of 60 minutes during school hours no later than one year after baseline
measurements. The students enrolled were to have opportunities to engage in physical
activity during PE lessons, recess and also during classes where physical activity
was to be integrated into various subjects on the general curriculum. The primary
objective of the intervention is in line with the current Icelandic physical activity
guidelines, which recommend that children partake in Moderate-to-Vigorous Physical
Activity (MVPA) for no less than 60 minutes every day of the week [18]. The guidelines are built upon evidence that suggests that at least one hour of MVPA
per day provides desirable health benefits for children and youth [19].

Our implementation approach was aimed at both encouraging teachers to perform physical
activity with their students and to build their necessary skills to become the implementers
of change needed to positively affect the children's lifestyles. This approach was
intended to serve as the bridge between theory (social cognitive theory) and intervention
effects. The researchers provided a platform for a reflective dialogue and discussion
of how these goals could be reached by means of collaborative effort and support.
The foundation of the collaborative approach harmonizes with the strategy labeled
as professional learning community (PLC). In brief, PLC is a learning platform promoting
collaborative learning amongst colleagues within the same work environment. It is
commonly defined as the community in a school where teachers and administrators continuously
seek and share learning and subsequently act on what they learn [20]. A number of attributes are present in such a community and the researchers' goals
were to have the participating teachers and principals all share the same vision and
values whilst working towards meeting the intervention objectives.

Bimonthly, throughout the intervention period, the investigators organized a workshop-meeting
where all the involved teachers from each intervention school met for about 2-3 hours.
These meetings had three main goals. Firstly, to provide an opportunity for the team
of teachers in all three intervention schools to meet and engage in dialogue with
their colleagues about the evolvement of the intervention. Secondly, these meetings
were intended to provide teachers with information and expert consultations on the
benefits of both physical activity and healthy lifestyle via informal lectures on
relevant topics. Thirdly, these meetings were to serve as platforms where teachers
and researchers would collectively work together to overcome various barriers related
to but not limited to the implementation and integration of physical activity into
daily life at each school.

The teachers at the intervention schools were provided access to physical activity
equipment intended to be used during regular school lessons. This included a cart
with different sized foam, plastic and rubber balls, different colored vests, and
cones. Teaching materials promoting physical activity, such as books and DVDs on classroom
workouts and cooperative activity games et cetera were also provided. One day of on-site
counseling led by a school-based PE expert was conducted at each school in the spring
of 2007, where teachers learned innovative approaches to integrating physical activity
into the daily curriculum. Thus, the teachers received input and ideas as to how they
could better utilize available equipment and the study material in their respective
environments. After the first year of intervention an additional PE lesson was introduced
at the intervention schools. The PE teachers at each of the intervention schools carried
out this additional lesson, which was specifically tailored to suit all children while
maintaining a high level of intensity. All six schools that participated in the study
followed the general physical activity curriculum, compulsory on the national level,
consisting of two 40-minute PE sessions per week, in addition to two swimming lessons
per week taught over the course of a six-week period any time during the school year.

Once each semester the investigators formally teamed up with the principals of the
three intervention schools to discuss the progress of the intervention. During these
meetings the researchers updated the principals on what had taken place during the
previous teacher meetings and encouraged a continuous on-site dialogue between the
principals and the teachers who implemented the intervention. In between the meetings
described above the researchers, teachers, and principals of the intervention schools
communicated via e-mail or phone.

Physical activity logbook

During the intervention period the teachers at each intervention school kept a log
of the estimated amount of supervised physical activity related behavior they carried
out with their students as a group (an assessment of the intervention implementation).
Thus, they estimated the number of minutes they engaged in any type of physical activity
during school hours, including PE lessons, swimming lessons, outdoor play/teaching
other than recess time, and active transport during school such as on field trips.
The mean minutes of supervised physical activity/day at school were calculated for
each school.

Group interviews with teachers

To identify important catalysts of and barriers to the intervention the researchers
conducted semi-structured group interviews in all three intervention schools in the
spring of 2008. All teachers (N = 11) in each school (n = 4 - 4 - 3) participated
and provided input. The teachers reflected on lessons learned throughout the process,
and on anything that affected the implementation of the intervention at the schools.
The teachers were also asked to comment on any changes in factors related to class
discipline, morale, and unity over the course of the study.

Primary outcome measures

Accelerometers were used (Actigraph™ GT1M monitors) to assess both volume and intensity
of physical activity during waking hours for seven consecutive days, five weekdays
and two weekend days. The sampling epoch time was 60 s. Measurements were performed
between mid-September and late November pre-intervention in the fall of 2006, in the
fall of 2007 and 2008. Measures were calculated for children that met the inclusion
criteria of having worn the accelerometer for at least 85% of the approximately 6-hour
long school day and a total of 10 hours per day, for a minimum of two weekdays. This
inclusion criteria allowed some flexibility in situations such as if children were
attending swimming lessons during school hours or failed to attach it back on after
such a lesson. Several cut-point thresholds for estimating MVPA in children by means
of accelerometers have been proposed [21-25], yet there is no consensus on where to place these MVPA cut-point values. We defined
MVPA as all activity above 2000 cpm as has been reported previously [26,27]. This cut-point is comparable with the one proposed by Evenson et. al [25], which was recently argued to have the best sensitivity/specificity ratio compared
to several other common cut-offs [28].

Covariates

Gender was recorded and height and weight were measured to the nearest 1 mm and 0.1
kg with participants wearing light clothing (t-shirt and underwear). Body mass index
(BMI, kg/m2) was calculated and the actual number used as a covariate in the multilevel models.

Data Analysis

We built multilevel regression models using R version 2.11.1 (http://www.r-project.org/webcite) to assess changes in objectively measured physical activity volume (cpm) and intensity
(MVPA) over time. This method of data analysis is appropriate wherever data is clustered
within groups, violating the independence of observations assumption [29]. Repeated measures are one example of such data structures and in our case the data
were also clustered within schools, implying that data points may be correlated both
within students as well as within schools.

Two types of multilevel-regression models were developed. Firstly, a basic model to
assess the intervention effects on physical activity with participants and schools
treated as random factors and group and time as independent variables. Secondly, an
adjusted model built upon the former model but with the addition of gender and BMI
as covariates (two and three way effect-measure modification was also assessed for
time, gender and BMI but only interactions yielding statistically significant results
were reported in the final models. Thus, these models estimated the variance of the
outcome measures by taking into account and allowing intercepts to vary within students,
random intercepts across students, and it allowed random intercepts for the six different
schools that participated in the study. The unconditional (no independent variables
- only random factors entered into the model) three-level models were run to estimate
the total variance at all three levels. The intraclass correlations can be defined
according to the proportion of variance that occurs at each level. The change in variance
from the unconditional model to the best conditional (adjusted) model at each level
can thus be presented as the percentage of variance explained at each particular level.

A priori, the study was powered to detect a medium effects size (0.25 SD units) of
any outcome measure with 80% probability, using ANCOVA to compare the post intervention
measurements adjusting for baseline, not taking the clustering within schools into
account. The sample size estimated was 175 children at the end of the study period.
We assumed a participation rate of 75% and due to the length of the study we assumed
an attrition rate of about 20%. Thus all 321 children entering second grade in 2006
from six schools were offered the chance to participate in order to provide sufficient
power to test the null hypothesis.

We ran an intention to treat analysis and all participants were included regardless
of how much time they accumulated in their respective class during the intervention
period between the fall of 2006 and fall of 2008. The multilevel analysis included
subjects with missing data points but imputation was not performed.

Results

A total of 196 children produced usable physical activity data after the first session
in 2006 while 52 children (16%) did not consent and 73 children (27%) failed to meet
the accelerometer criteria set forth prior to the study (described above). Similarly,
224 children yielded usable data after the session in 2007, 78 new participants entered
the study at that time point, but 50 children (25%) were lost to follow up from the
year before, either due to failing to meet accelerometer criteria or they did not
participate in the measurements. At the end of the study period 239 children produced
usable data, 35 of whom had either not produced usable data in the year before and
entered the study again, or entered for the first time. However, 20 children (9%)
from the previous year were lost due to their failure to meet the accelerometer criteria
or due to not participating in the measurements.

Baseline status

Table 1 shows the characteristics of the study population at baseline. There was a statistically
significant difference in BMI between the two study groups at baseline, where children
of the control group had higher mean BMI value (95%CI; 0.08, 1.16) (Table 1.). Data on socioeconomic status (SES) estimated via questionnaire in the fall of
2006 and fall of 2008 suggested no difference between the study groups in median income
of the parents, but only about half of the study population answered the question.

Physical activity - accelerometers

Two basic models showing the estimated unadjusted effects of the intervention on physical
activity cpm during school and minutes of MVPA during school hours are shown in Table
2. Children in the intervention schools were significantly more active after one year
of intervention (at the mid-point of the intervention period) compared to children
in the control schools (p > .0001), but there was no significant difference in either
volume (p = .10) or intensity (p = .71) of physical activity at the end of the two-year
study period. Analogous models, but adjusted for the effects of gender and BMI, are
shown in Table 3. These models are complemented by the trajectories depicted in Figure 2 and Figure 3, which show the true median values in the non-transformed units. The results for
the adjusted models were analogous to those for the basic models and showed significant
difference in volume of physical activity (cpm) during school hours (p > .0001) after
one year of intervention, but no difference at the end of the two-year intervention
period (p = .61). In addition the adjusted model showed that boys were more active
compared to girls (p > .0001) and children with higher BMI were less active than children
with lower BMI (p = .01), independent of study group and time. The adjusted model
for minutes of MVPA during school hours showed analogous results, but with the addition
of a significant three-way interaction between time at mid-point, group and gender
(p = .02). Thus, the intervention children accrued significantly more minutes of MVPA
during school hours after one year of intervention (p > .0001) but the increase was
significantly greater in boys compared to girls (p = .02), by about 10 minutes (Figure
2). The adjusted multilevel model for square-root-transformed cpm explained 20.6% of
the variance existing at the school level, 24.6% of the variance at the child level,
but less of the within-child variance, or 10.5%. Similarly, the adjusted model for
the square-root-transformed MVPA during school hours explained 14.1% of the total
variance at the school level, 29% of the variance at the child level, and mere 6.6%
of the within-child variance.

Table 2. Physical activity cpm during school hours (square root transformed) is shown as a
function of time, group status, BMI and sex. Repeated measures mixed effects models
were built to contrast the two study groups, intervention vs. control, over time with
regard to physical activity during school time, controlling for the clustering of
data structure.

Table 3. Minutes of MVPA during school hours (square root transformed) is shown as a function
of group status, time, BMI and sex. Repeated measures mixed effects unconditional
vs. conditional models controlling for the clustering of data structure contrast the
two study groups over time with regard to time spent in MVPA during school hours.

Figure 2.Median cpm during school hours at baseline 2006, fall 2007, and post intervention
in 2008 with estimates of the 95% CI around the median.

Figure 3.Median minutes of MVPA during after-school hours at baseline in 2006, fall 2007, and
post intervention in 2008 with estimates of the 95% CI around the median

The same types of models (basic and adjusted) were run to observe possible change
in cpm and minute of MVPA during after-school hours on weekdays over time. The unadjusted
trajectories are depicted in Figure 4 and Figure 5. The adjusted model for cpm during after-school hours yielded no significant difference
between intervention and control schools at baseline (p = .33), at mid-point (p =
.09) or at the end of the intervention period (.91). However, boys were more active
than girls (p = .001) during after-school hours and those with higher BMI were less
active (p = .02), independent of study group and time. Similarly, the adjusted model
for the square-root-transformed minutes of MVPA during after-school hours showed no
significant difference between the two study groups at baseline (p = .58), at mid-point
(p = .59) or at the end of the study period (p = .50). Boys accrued on average more
minutes of MVPA during after-school hours compared to girls (p > .0001), but there
was no difference in minutes of MVPA during after-school hours by value of BMI (p
= .40), independent of study group and time. It should be noted that conducting the
analyses above on the original cohort only, excluding children who had missing values
of data at any of the three time points, yielded comparable results, but with power
too low to detect some of the significant relationships detected by the models described
above.

Figure 4.Median cpm during school hours at baseline 2006, fall 2007, and post intervention
in 2008 with estimates of the 95% CI around the median.

Figure 5.Median minutes of MVPA during school hours at baseline in 2006, fall 2007, and post
intervention in 2008 with estimates of the 95% CI around the median.

Physical activity during school hours - subjective assessment of implementation

The estimated mean minutes of supervised/integrated physical activity conducted by
teachers in each intervention school per day are depicted in Figure 6 (overall mean, and mean for each school). These results suggested an upward trend
in physical activity implementation conducted during school hours over the course
of the study but with a drop in physical activity implementation at the end of the
study.

Figure 6.Subjective estimation from teachers' physical activity log book of time spent doing
physical activity (under teacher's supervision) at school following baseline measurements
in 2006 until end of intervention period. Each of the intervention schools started their respective intervention following
the baseline-measurements. Data is not shown for September 2006, May 2007 and October
2009 because only one or none of the intervention schools registered physical activity
during those months. The dark squares represent the time during which physical activity
was being assessed with accelerometers.

Findings listed as key themes that were identified during teacher interviews in the
spring of 2008, along with sample quotes from the teachers involved in intervention
implementation, are shown in Table 4. Both groups of teachers were generally positive when evaluating their experiences
during the time they implemented the intervention. Overall they enjoyed the progressive
implementation approach of the intervention allowing time for on-site trial and error.

Table 4. Results showing common themes that came up during three semi-structured interviews
where benefits, facilitators and barriers of the intervention implementation were
discussed

Discussion

Results from accelerometers showed children in the intervention schools being more
active compared to those in control schools after one year of intervention. The difference
at that time point was driven by boys in the intervention group, who at that point
had increased their amount of MVPA significantly more than the intervention girls.
No group difference was detected at the end of the intervention period a year later.
Boys in both groups were consistently more active than girls at all three time points,
and those children with higher BMI were less active during school hours and after
school hours, but there was no association between BMI and physical activity during
after-school hours.

It is important to evaluate the intervention process of every intervention study conducted
before the efficacy of the program on other biological or social variables is assessed.
Was the intervention conducted as planned, and if so, to what extent were the objectives
met? To our knowledge no study has used the combination of methods described herein
to assess changes in school-related physical activity during a two-year school-based
intervention program. It strengthens the results that there seems to be harmony between
both objective assessment of physical activity and subjective assessment of physical
activity implementation, to the extent that they can be compared. Both measurements
show a parabolic curve-shape when the three time points where physical activity was
objectively assessed are contrasted. Perhaps these findings are positive because objective
and subjective measurements have often showed inconsistent, even contradictory, results,
both in observational and experimental studies [11,30].

The purpose of the extra PE lesson in the second year of the intervention was to considerably
increase the amount of time where all participating children would get an opportunity
to partake in physical activity of greater intensity. However, it seems clear that
the increase in number of minutes engaged in MVPA during school hours in the fall
of 2007 is driven by the boys being considerably more active at moderate-to-vigorous
intensity, by on average about 10 minutes during school hours. These results are somewhat
in line with results from the M-SPAN study, which conducted a two-year intervention
focused on an environmental and policy-driven approach in middle schools in San Diego
County, California where they did not see positive intervention effects on physical
activity in girls [31]. The authors claimed that challenges were anticipated since girls are generally less
active than boys but the reasons for these differential effects were nevertheless
unclear. Otherwise, there is little evidence for boys and girls responding differently
to school-based interventions as well as to different components of the interventions
[7]. Our results nonetheless do suggest a future effort be made to test various gender-specific
strategies given the gender-specific differences in the determinants of physical activity
[32-34] and the results presented here. These results are nonetheless disappointing because
the teachers reported during interviews that they had emphasized activities that they
intended to be equally suitable for both genders.

Studies have previously reported conclusive evidence for gender specific differences
concerning the amount of physical activity performed by children and adolescents [35-37], which is also confirmed at all time points in this study. In light of this fact
we emphasized the importance that activities performed during PE and during regular
class hours would suit boys and girls equally. None of the classroom teachers (all
female) reported they had experienced gender differences in participation in the numerous
activities performed during the intervention phase when asked specifically about it
during the group interview sessions in the spring of 2008. However, there are several
plausible explanations for this seemingly different response between the genders.
First, the teachers' assessment may be wrong! Secondly, perhaps girls were not as
active as boys during recess periods, when the children were not under surveillance
by their teachers, in the fall of 2007. Another explanation may partly lie in how
differently boys and girls may perceive barriers and facilitators of physical activity.
A recent study of 350 adolescents in Maryland in the US, showed that when it came
to performing physical activity, adolescent girls were more sensitive to their environment
and perceived more barriers than boys [38]. If this holds true for younger children then perceived environmental barriers may
have contributed to this differential rate of increase in MVPA during school hours
in fall of 2007. It is also worth mentioning that results from other intervention
studies that have used objective measures to assess MVPA have shown significant increase
in MVPA after and during the intervention, but do not show differential intervention
effects on intensity nor volume between boys and girls [14,15].

There are several possible explanations for the drop in school-related physical activity
recorded by the teachers at the end of the study. We believe that the primary reason
for this is that only two of the initial eight general teachers were still part of
the study team at that time, while six of the teachers were either on maternity leave
or had started teaching a different class. The majority of the new teachers had only
received minimal training during a mere one meeting prior to the measurements being
conducted in the fall of 2008. Another contributing factor to this drop could be that
the extra PE lesson/week introduced in the fall of 2007 was no longer available to
the children at the intervention schools. This may have significantly affected the
amount of MVPA the children received during school hours. The intervention did not
seem to have any effect on physical activity during after-school hours because no
significant difference in volume (cpm) or intensity (minutes of MVPA) of physical
activity was detected during this time of the day. This seems to be consistent with
what Dobbins et al. concluded in their review that there is no evidence for positive
effects of school-based physical activity interventions on leisure time physical activity
in children [7].

Some of the strengths related to the implementation of this intervention are in line
with strengths of comparable intervention studies [14]. First, the results from the teacher interviews during the intervention phase may
suggest that empowering the teachers to become effective implementers of positive
change in physical activity during school hours may partly explain the increase. Second,
the progressive intervention allowed for the possibility of on-site trial and error
while the implementers slowly built up their skill set, enabling them to increase
school-based physical activity throughout the school day. Third, this method respects
a teacher's independence, as it allows individual teachers to adjust the physical
activity-related activities at their own will. Finally, it is worth mentioning that
the use of accelerometers as an objective measure of school-based physical activity
eliminated the possibility of self-report bias, and using hierarchical models to analyze
these results is an appropriate technique taking into account the clustered data structure.

There are methodological limitations to this study that must be addressed. Measuring
school-based physical activity at the end of each school year, similar to what was
done at the beginning of each school year, would likely have provided stronger indications
of the intervention progression. Thus, while having three objectively obtained physical
activity data points can be viewed as strength, an additional two in the spring of
2007 and spring of 2008 would have strengthened our inferential ability. Despite all
the children being a similar age, the study population was relatively small, thus
limiting the potential to generalize the findings. Further, we cannot state which
specific part of the intervention contributed more than others to the overall increase
in physical activity during school hours in the fall of 2007, i.e. if it was the extra
PE lesson or integrated physical activity within the various general school subjects.
It has also recently been pointed out that having the accelerometers record 60 s epoch
is likely to have resulted in a less accurate estimation of physical activity than
using shorter epoch like 15 s [39]. This may have underestimated the amount of MVPA the children performed during school
hours. Finally, the lack of consensus on where to place accelerometer cut-points defining
moderate-to-vigorous physical activity limits our ability to accurately classify physical
activity intensity.

Conclusions

The results suggest that the primary objective of increasing physical activity during
school hours was met after one year of intervention, although to a varying degree
within the intervention schools and more pronounced among boys. However, no increase
in physical activity was observed at the end of the study period, suggesting that
any increase in physical activity during school hours may be highly linked to the
motivation and training of general teachers. In general boys are more active than
girls and may even respond better to school-based intervention compared to girls.
Also those with higher BMI are less active during school-hours. Designs of school-based
interventions should take this into consideration in order to maximize the effects
of increased physical activity among all children.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

KTM carried out the statistical analysis, he contributed to the work involving the
study design and he drafted the manuscript. KTM made the greatest contribution to
this paper. IS contributed to the study design, project planning, and he was involved
in the intervention assessment throughout the study period. TS participated in the
statistical analysis and provided guidance during the writing process of this paper.
EJ was the project leader and participated in all parts of the work. All authors provided
critical revision of the paper and read the final manuscript. All authors read and
approved the final manuscript.

Acknowledgements and funding

The authors wish to thank all the participants and their families for giving their
time and energy to undergo all the different measurements conducted over the course
of this study. We would also like to thank the staff at each of the participating
schools for their invaluable assistance during the study, their hospitality and helpfulness.
This work was supported by the Icelandic Research Fund and the Technology Development
Fund administered by Rannis, the Icelandic Centre for Research.